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    Genome Res. 2010 Feb;20(2):190-200. Epub 2009 Dec 9.

    Bayesian network analysis of targeting interactions in chromatin.

    van Steensel B, Braunschweig U, Filion GJ, Chen M, van Bemmel JG, Ideker T.

    Source

    Division of Gene Regulation, Netherlands Cancer Institute, 1066 CX Amsterdam, the Netherlands. b.v.steensel@nki.nl

    Abstract

    In eukaryotes, many chromatin proteins together regulate gene expression. Chromatin proteins often direct the genomic binding pattern of other chromatin proteins, for example, by recruitment or competition mechanisms. The network of such targeting interactions in chromatin is complex and still poorly understood. Based on genome-wide binding maps, we constructed a Bayesian network model of the targeting interactions among a broad set of 43 chromatin components in Drosophila cells. This model predicts many novel functional relationships. For example, we found that the homologous proteins HP1 and HP1C each target the heterochromatin protein HP3 to distinct sets of genes in a competitive manner. We also discovered a central role for the remodeling factor Brahma in the targeting of several DNA-binding factors, including GAGA factor, JRA, and SU(VAR)3-7. Our network model provides a global view of the targeting interplay among dozens of chromatin components.

    PMID:
    20007327
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC2813475
    Free PMC Article

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